characterizing turbulence at a prospective tidal energy site: observational data analysis
DESCRIPTION
Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis. Katherine McCaffrey PhD Candidate, Fox-Kemper Research Group Department of Atmospheric and Oceanic Sciences Cooperative Institute for Research in Environmental Sciences. - PowerPoint PPT PresentationTRANSCRIPT
![Page 1: Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis](https://reader036.vdocuments.mx/reader036/viewer/2022070410/56814664550346895db3844d/html5/thumbnails/1.jpg)
1
CHARACTERIZING TURBULENCE AT A PROSPECTIVE TIDAL ENERGY SITE: OBSERVATIONAL DATA ANALYSIS
Katherine McCaffrey
PhD Candidate, Fox-Kemper Research Group
Department of Atmospheric and Oceanic Sciences
Cooperative Institute for Research in Environmental Sciences
Thank you to my advisor and collaborators:
Baylor Fox-Kemper, Dept. of Geological Sciences, Brown University, CIRES
Peter Hamlington, Dept. of Mechanical Engineering, CU Boulder
Jim Thomson, Applied Physical Laboratory, Univ. of Washington
![Page 2: Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis](https://reader036.vdocuments.mx/reader036/viewer/2022070410/56814664550346895db3844d/html5/thumbnails/2.jpg)
2
Outline
• Introduction to Tidal Energy• Introduction to the Problem• Anisotropy, Coherence, and Intermittency
• Observations and Metrics• Parameterization Results
• Preliminary Statistical Model Results
![Page 3: Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis](https://reader036.vdocuments.mx/reader036/viewer/2022070410/56814664550346895db3844d/html5/thumbnails/3.jpg)
3
Tidal Energy Resource• Clean, renewable, predictable energy source; close to
population centers• DOE Resource Assessment: potential 250 TWh/year
electricity generation (~6% of US usage)
http://www.tidalstreampower.gatech.edu/
![Page 4: Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis](https://reader036.vdocuments.mx/reader036/viewer/2022070410/56814664550346895db3844d/html5/thumbnails/4.jpg)
4
Tidal Energy Conversion Technology• Barrages - use pressure differences on either side of a dam
• In-Stream Turbine – in the flow, invisible from surface
http://www.infoniac.com/environment/world-s-biggest-tidal-turbine-to-be-built-in-scotland.html
http://w
ww
.darvill.cla
ra.n
et/alte
ne
rg/
tidal.h
tm
http://w
ww
.thee
colo
gist.org/N
ew
s/n
ew
s_a
nalysis/
67
808
ho
w_
france
_e
clipse
d_th
e_
uk_
with
_britta
ny_
tidal_
succe
ss_story.htm
l
Rance, France – first and largest tidal barrage in the world: 240 MW
![Page 5: Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis](https://reader036.vdocuments.mx/reader036/viewer/2022070410/56814664550346895db3844d/html5/thumbnails/5.jpg)
5
Where are we now?
• Bay of Fundy – successes and setbacks
• European Marine Energy Centre, Orkney, Scotland test center
• Thorough site characterizations at Admiralty Inlet and Nodule Point, Puget Sound, WA
![Page 6: Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis](https://reader036.vdocuments.mx/reader036/viewer/2022070410/56814664550346895db3844d/html5/thumbnails/6.jpg)
6
Learning from Wind• Turbulence effects on power
production: turbulence intensity
• Turbulence effects on turbine mechanics (loads and subsequent gear box failures): coherent turbulent kinetic energy
Kaiser et al 2007
Kelley et al 2005
Wind speed
Pow
er
Red – CTKEBlue – Dynamic Pressure
Time (seconds)
Local Relative Energy Flux
Local Dynamic Pressure Response
Local CTKE Excitation
![Page 7: Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis](https://reader036.vdocuments.mx/reader036/viewer/2022070410/56814664550346895db3844d/html5/thumbnails/7.jpg)
7
Goals
• Take the knowledge and experiences of the wind energy industry to further the development of tidal energy, focusing on turbulence.
• Do a thorough physical description of the turbulence that will affect a tidal turbine• Site classification for decision-making• Describe realistic turbulence with metrics that can be
used to improve models• Turbulent in-flow generators: National Renewable Energy
Laboratory’s TurbSim/pyTurbSim• Tidal Array scale: ROMS• Turbine scale: LES
![Page 8: Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis](https://reader036.vdocuments.mx/reader036/viewer/2022070410/56814664550346895db3844d/html5/thumbnails/8.jpg)
8
Nodule Point, Puget Sound, WA
Latitude N 48 01.924’
Longitude W 122 39.689’
Depth 22m
DatesFeb 17-21,
2011
Sampling Frequency
32 Hz
Noise 0.02 m/s
Proposed Hub Height
4.7m
Hub Height Max. Velocity
1.8 m/s
Thomson et al, 2012
![Page 9: Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis](https://reader036.vdocuments.mx/reader036/viewer/2022070410/56814664550346895db3844d/html5/thumbnails/9.jpg)
Turbulence Metrics• Turbulence Intensity:
• Coherent Turbulent Kinetic Energy:
9
Mean u (m/s)I u (
%)
StD
ev u
(m
/s)
![Page 10: Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis](https://reader036.vdocuments.mx/reader036/viewer/2022070410/56814664550346895db3844d/html5/thumbnails/10.jpg)
10
• Anisotropy Tensor
Invariants:
• CTKE-like, but built from invariants: Anisotropy Magnitude• Independent of chosen coordinate system
All real flows fall somewhere in this triangle
Turbulence Metrics
Three component limit
One component limit
Two component limit
![Page 11: Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis](https://reader036.vdocuments.mx/reader036/viewer/2022070410/56814664550346895db3844d/html5/thumbnails/11.jpg)
11
Physical Turbulence• What physical features are there to turbulence?
• Size – how big? The size of the turbine? Larger? Smaller?• Frequency – how often do these “events” happen?• Shape – flat, pancake-like? 3-d
• How do we measure these?• Coherence – how long is the flow correlated?• Intermittency – how “random” is the flow? • Anisotropy – how many velocity components contribute to the
fluctuating velocity?
![Page 12: Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis](https://reader036.vdocuments.mx/reader036/viewer/2022070410/56814664550346895db3844d/html5/thumbnails/12.jpg)
Coherence• Temporal Autocorrelation
• Integral Scale
• Taylor Scale
12
τ (seconds)
R(τ
) (%
)
Λ=10.13 secλ=0.08 sec
![Page 13: Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis](https://reader036.vdocuments.mx/reader036/viewer/2022070410/56814664550346895db3844d/html5/thumbnails/13.jpg)
IntermittencyIntermittency manifests itself in departures from a normal
distribution in the probability density function of velocity differences.
13
Pdfs of the velocity perturbation differences, ∆u’ (circles), ∆v’ (squares), and ∆w’ (diamonds), with Gaussian curves for reference (dashed). Black shapes have a time step of ∆t = 1 (~3 cm), gray are ∆t = 115 (~3 m), and white are ∆t = 230 (~6 m).
Higher order moments support the lack of Gaussianity in the pdfs.
Mean
Kurtosis
Skewness
Standard Deviation
Δu/σ
Pro
babi
lity
![Page 14: Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis](https://reader036.vdocuments.mx/reader036/viewer/2022070410/56814664550346895db3844d/html5/thumbnails/14.jpg)
Anisotropy• Improvement to the anisotropy analysis: For eigenvalues, λi, of the anisotropy tensor, aij, ordered from greatest to least, the barycentric coordinates are defined by:
14
Banerjee et al 2007
C1c : one-component limit – linear
C2c : two-component limit – planar
C3c : three-component limit – isotropic
Three component limit
Two component limitOne component limit
![Page 15: Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis](https://reader036.vdocuments.mx/reader036/viewer/2022070410/56814664550346895db3844d/html5/thumbnails/15.jpg)
15
Parameterization• How do we represent how “turbulent” a location is?
• Often turbulence intensity is all that is used• What about intermittency, coherence, and anisotropy?
Mean u (m/s)
I u (
%)
A (
m2 /
s2 )
A (
m2 /
s2 )
CTKE (m2/s2)
![Page 16: Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis](https://reader036.vdocuments.mx/reader036/viewer/2022070410/56814664550346895db3844d/html5/thumbnails/16.jpg)
Parameterization: Shape
16
Iu only measures one component (u)
A (
m2 /
s2 )
The highest instance of each parameter (large shapes) is close(r) to the one-component limit.
I u (
%)
CT
KE
(m
2 /s2 )A is better than CTKE
Three
One Two
![Page 17: Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis](https://reader036.vdocuments.mx/reader036/viewer/2022070410/56814664550346895db3844d/html5/thumbnails/17.jpg)
Parameterization: Size
λ Λ
Iu 0.596 0.450
CTKE 0.680 0.017
A 0.884 0.317
17
The anisotropy magnitude, A, captures the the behavior of CTKE (and therefore loads?), intermittency in the pdf, the shape from the barycentric map, and the coherence of the correlation function.
A (
m2 /
s2 )
λ (seconds)
![Page 18: Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis](https://reader036.vdocuments.mx/reader036/viewer/2022070410/56814664550346895db3844d/html5/thumbnails/18.jpg)
18
Conclusions• A new, tensor-invariant metric for physically describing
turbulence, the anisotropy magnitude, is introduced• Turbulence intensity does not parameterize intermittency,
coherence, or anisotropy as well as other easy-to-measure metrics such as CTKE and A.
• The anisotropy magnitude does the best job at representing intermittency, coherence, and anisotropy.
• If A is similar to CTKE, does it have the same strong correlation to turbine loads?
• How well does the coherence function in pyTurbSim represent the observations in terms of A?
![Page 19: Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis](https://reader036.vdocuments.mx/reader036/viewer/2022070410/56814664550346895db3844d/html5/thumbnails/19.jpg)
19
Next step…
• The NREL pyTurbSim model (Jonkman & Kilcher) creates stochastic turbulence.
• The NCAR LES model (Sullivan et al.) includes more realistic ocean physics.
J. Jonkman, L. Kilcher, TurbSim user’s guide: Version 1.06. 00, Golden, CO: National Renewable Energy Laboratory (2012).P. P. Sullivan, J. C. McWilliams, C.-H. Moeng, A subgrid-scale model for large-eddy simulation of planetary boundary-layer flows, Boundary Layer Meteorology 71 (1994) 247–276.
How well do the models do at generating realistic turbulence?
How do the statistics calculated from the model output compare to those from the observations?
![Page 20: Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis](https://reader036.vdocuments.mx/reader036/viewer/2022070410/56814664550346895db3844d/html5/thumbnails/20.jpg)
20
Introduction to pyTurbSim
• Stochastic turbulence generator• Inputs:
• Background mean flow profile• Spectral density curve• Turbulence intensity and Reynolds stresses
• Method:• Inverse fast Fourier transform• Optional additional spatial coherence function
• Outputs:• Three-component velocity time series
Model Input
Latitude 48N
Depth (RefHt) 22m
Uref 1.8 m/s
Sampling Frequency (timestep)
10 Hz
Hub Height 4.7m___________________
u’w’ .0011 m2/s2
__________________
u’v’ .0009 m2/s2
_____________________
v’w’ .0004 m2/s2
Turb Model TIDAL
Profile Type H2L (log)
![Page 21: Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis](https://reader036.vdocuments.mx/reader036/viewer/2022070410/56814664550346895db3844d/html5/thumbnails/21.jpg)
21
![Page 22: Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis](https://reader036.vdocuments.mx/reader036/viewer/2022070410/56814664550346895db3844d/html5/thumbnails/22.jpg)
22
Preliminary Results• Baseline statistics, before coherence is added
A (
m2 /
s2 )
Iu (%)
CT
KE
(m
2 /s2 )
CTKE (m2/s2)
A (
m2 /
s2 )
![Page 23: Characterizing Turbulence at a Prospective Tidal Energy Site: Observational Data Analysis](https://reader036.vdocuments.mx/reader036/viewer/2022070410/56814664550346895db3844d/html5/thumbnails/23.jpg)
23
Thank you!
• Stay tuned for model results at the Boulder Fluid Seminar December 10th!